Animal Genetics and Improvement

Code:

MV214

Acronym:

GMA

Keywords
Classification	Keyword
OFICIAL	Animal Production

Instance: 2009/2010 - 1S

Active?	Yes
Responsible unit:	Population Studies
Course/CS Responsible:	Integrated Masters Degree in Veterinary Medicine

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MIMV	121	Plan 2007 to 2017	2	-	5	64	135

Teaching language

Portuguese

Objectives

Besides fundamental concepts on animal genetics, the student should know how to estimate genetic parameters, make simple genetic evaluations, compute breeding values, define objectives and criteria for developing selection programs, calculate genetic progress by unit of time, work with concepts and establish programs to minimize loss of genes in small populations.

Program

Mendelian Genetics: Pure breeds, hybridization. Allelic theory and independent segregation. Dominance, homozygous and heterozygous. Phenotype, genotype and environment. Probability and events. Confidence interval. Codominance, nondisjunction, lethal genotypes, multiple alleles, epistasis. Sex linkage, sex-influenced and sex-limited traits. Linkage, crossing-over and recombination, genetic maps. Testing genetic hypothesis.
Population Genetics: Gene and genotypic frequencies. The Hardy-Weinberg Law. Mutation, migration, selection, nonrandom mating. Probability of detection carriers. The single locus model. Selection and selection response. Breeding value. Average effect of a gene substitution. Dominance deviation.
Quantitative Genetics: Quantitative traits, the genetic model, environmental effects and epistasis. Animal improvement strategies. Partition of the phenotypic variance. The normal distribution. Covariances, correlations and regressions. Partition of the genetic variance; heritabilities in broad and narrow sense. Repeated traits, permanent and temporary environmental effects; repeatability and prediction of future records. Direct and collateral genetic relationships. Computing inbreeding and additive relationships. Genetic regression on the phenotype. Prediction of breeding values. Accuracy of prediction. Genetic evaluations with different sources of records. Response to selection (genetic progress per generation and year), selection differential, selection intensity. Alternative selection programs. Selection of more than one trait, correlated response. Mating strategies. Inbreeding and linebreeding. Crossbreeding, heterosis. Synthetic breeds. Maintenance of small populations. Founders, minimizing the probability of gene losses. Population effective size and inbreeding.
Principles of Animal Breeding: The genetic model. Variances and covariances with interess for animal breeding. Expected values. Dominance and additive genetic relationships matrices. Interpretation of covariances. ANOVA. Models of one effect, partition of the variance components. Sire model, repeatability model, variance estimators and intraclass correlation. The animal model, expected values and variance components. Equivalent models.

Mandatory literature

Vleck L. Dale Van; Genetics for the animal sciences (fot.). ISBN: 0-7167-1800-6

Complementary Bibliography

Mrode R. A.; Linear models for the prediction of animal breeding values. ISBN: 0-85198-996-9
Vleck L. Dale van; Selection index and introduction to mixed model methods. ISBN: 0-8493-8762-0
Chapman A. B. ed.; General and quantitative genetics. ISBN: 0-444-41836-9
Pirchner, F; Population Genetics and Animal Breeding
Falconer D. S.; Introduction to quantitative genetics. ISBN: 0-582-24302-5

Teaching methods and learning activities

Theoretical and Pratical classes.

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Description	Type	Time (hours)	Weight (%)	End date
Attendance (estimated)	Participação presencial	60,00
Practice for lab work	Teste	42,00
	Total:	-	0,00

Amount of time allocated to each course unit

Description	Type	Time (hours)	End date
Preparing for the Exame	Estudo autónomo	33
	Total:	33,00

Eligibility for exams

Students must attend to practical lessons, at least 25% of them.

Calculation formula of final grade

Written final examination with theoretical content (90%) and lab exercises (10%). Minimum score of 9.5 points on the theoretical part.